DIANA-mAP – analyzing miRNA from raw RNA sequencing data to quantification

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell.

Researchers from the University of Thessaly have developed DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge.

DIANA-mAP preprocessing workflow


It is composed of three individual steps: In the Data Acquisition step, the user can download publicly available datasets from online repositories by providing their accession numbers. The Adapter Detection step either uses a provided adapter sequence or scans the dataset in order to infer the adapter sequence and identify it. The Quality Trimming/Adapter Removal step removes from the dataset low-quality sections and full or partial adapter sequences in order to cleanse the dataset for further analysis.

Availability – DIANA-mAP is free to use under the MIT License and can be acquired through GitHub (https://github.com/athalexiou/DIANA-mAP), It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

Alexiou A, Zisis D, Kavakiotis I, Miliotis M, Koussounadis A, Karagkouni D, Hatzigeorgiou AG. (2021) DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification. Genes 12(1), 46. [article]

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